In modern society and throughout recorded history, there has always been a demand for security measures. Such measures have been used to prevent theft, unauthorized access to sensitive materials and areas, and in a variety of other applications. One such common security measure includes intrusion detection systems. Typically, intrusion detection systems incorporate video surveillance that includes monitoring video feeds acquired by one or more video cameras that are situated around a perimeter of a facility sought to be protected. The monitoring of the video feeds is typically accomplished by a human, such as by security personnel or by the police. However, because potential security threats are isolated events amidst long, otherwise uneventfull time spans, boredom can be a significant problem, thus resulting in lapses of security.
To overcome the problem of boredom, some automated intrusion detection systems have been developed. Such automated systems can incorporate various computer vision algorithms to assist human monitoring. Typically, a change detection algorithm is used to identify regions within the monitored area that may merit more careful review by the monitoring human. However, such systems can be highly prone to registering false positives, such as resulting from environmental variation, for example distant background changes, wind-blown shrubbery, camera vibration, changing brightness from passing clouds, and moving light beams at night. As such, the resultant high rate of false positives can fatigue even the most experienced human security monitors. To overcome the false positive conditions, some systems may allow an operator to draw null zones that prohibit activity in the null zone from tripping the alarm. However, such a solution can provide an opportunity for a false negative result, thus resulting in a lapse in security.
In addition to the problems associated with boredom, typical automated intrusion detection systems can suffer from a number of additional drawbacks. For example, camera based intrusion detection systems typically include a camera that is mounted at a greatly elevated position looking down. As such, it can determine a location of an intruder based solely on the location of the intruder on the ground within the field of view of the camera. However, such an arrangement can be difficult to install and maintain, and can be expensive by requiring special mounting equipment and accessories. In addition, such systems may have a limited field of view. As such, an intruder may be able to see such systems before the intruder is detected, thus allowing the intruder an opportunity to take advantage of blind-spots, or devise other counter-measures to defeat the automated intrusion detection system.